This is a very interesting and important question. A Data Warehouse (DWH) is the systematic storage of data in a data model structure based on specific customer business requirements agreed during the analysis. A data model is a multidimensional space within which the stored data can be analysed (dimensions can be, for example, centre, partner/counter-party, project, vehicle, company, segment, etc.) and indicators (in other words, indicators, metrics), i.e., material content (turnover or stock, expressed in money (amounts, e.g., sales price, purchase price, average price), quantity (pieces, kg., meters, etc.). Dimensions from the BI/reporting perspective are not necessarily dimensions from the HELIOS perspective (e.g. in finance – here there is no need to account for every reporting dimension, some can be derived based on additional embedded logic or as an attribute of the original dimension (e.g. belonging to a territorial segment can be derived from the customer address).

Importantly, the data warehouse allows any combination of dimensions and indicators to be analysed in detail. In a simpler case, the way of building a view may resemble working with a contingency table in Excel. However, a standard feature of reporting is the ability to define custom reports where each row can be an intersection of the required dimensions and indicators. In addition, the reports can be added to with other derived calculated rows/indicators within the definition. Thus, within the data model, any report/view in the form of a table or chart, including formatting/conditional formatting, can be quickly and easily created by the user by combining dimensions and indicators. All tables and charts contain active elements / can be easily analysed in detail via the Group By and Drill To Detail functions.